Comparison · RedactSure Research
Chris Sowa · Founder, RedactSure
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RedactSure vs Infisical: 2026 Comparison & Alternative
Infisical Agent Vault attaches stored credentials to an agent's request at a proxy; RedactSure, an Infisical alternative built for AI agents, replaces values on the screen before the model reads it. RedactSure is an alternative way to think about agent browsing security, because it protects sensitive data as it is rendered on a screen, before an agent uses it.
A support lead has a customer account open in the console her team bought, with a card number and a call note on the screen, and the agent she is training is about to read it, which is where an Infisical alternative comes in. Infisical Agent Vault works at the network edge, where a forward proxy attaches the real credential to the agent's request and the agent never holds it. RedactSure replaces the name, the card number and the API token with consistent stand-ins before the model reads anything.
This page quotes Infisical's Agent Vault overview and the post that introduced the product, and follows one record: a customer account in a support console, where the account page carries a card number and a call note and the settings page an API token. What Is Render-Layer Tokenization? defines the substitution at issue; What Is Least Exposure? explains why a model's view should stop at the task.
Key findings
- As an Infisical alternative for agent work, RedactSure replaces values on the rendered page before any model reads it, so the agent works with CUST_001 and TOKEN_001 and the real values are released only at an approved destination (What Is Render-Layer Tokenization?).
- Values replaced before the model reads them keep a record out of reach, because an injected instruction works through what the page says: such attacks can "enable adversaries to remotely (without a direct interface) exploit LLM-integrated applications" (Greshake et al., 2023).
- None of Infisical's pages describes a control over what a model reads on a rendered page; the Agent Vault post covers the request its proxy attaches a credential to, not the screen the record is drawn on (Infisical, Proxy, 2026).
- Infisical's Agent Vault overview describes "Forward proxies that intercept an AI agent's requests and attach real credentials on the way out" and "Time-bound grants that let AI agents access services without holding real credentials" (Infisical, Documentation, 2026).
- The post is plain about the boundary: "In short, the agent should not be trusted with direct access to any secrets," and "To solve this, Agent Vault terminates TLS," which puts the plaintext in the proxy rather than in the agent (Infisical, Proxy, 2026).
How do the two compare side by side?
The rows pair Infisical's own wording with the behavior a governed environment provides at the same point, and the last column gives the buyer something to check.
| Dimension | Infisical, per its pages | RedactSure | What to verify |
|---|---|---|---|
| Where the control sits | "Forward proxies that intercept an AI agent's requests and attach real credentials on the way out" (Infisical, Documentation, 2026) | On the screen the agent works in, before any model reads it | Where a value is replaced |
| How coverage starts | A grant issued for the call, with "Time-bound grants that let AI agents access services without holding real credentials" (Infisical, Documentation, 2026) | The agent works inside the governed environment, and the application is unchanged | What covers a screen outside that path |
| What the model receives | A request with the real credential inserted, because "the agent should not be trusted with direct access to any secrets" (Infisical, Proxy, 2026) | The screen with tokens such as CUST_001 and TOKEN_001, consistent for the whole run | One screen, exactly as the model saw it |
| How real values are restored | "To solve this, Agent Vault terminates TLS," so the proxy places the value in the request (Infisical, Proxy, 2026) | Released at an approved destination when a named person approves the action | Who authorizes it |
| Who approves an action | A time bound: "Time-bound grants" and no named approver for the action (Infisical, Documentation, 2026) | A named person approves every payment, submission and record change | A person's name, not a rule |
| The audit record | The calls the proxy handled, and no record of the screen (Infisical, Documentation, 2026) | Every screen as tokens, every action and every approval, exported to the customer's SIEM | Whether the record shows what the model saw |
The two middle columns answer different questions: whether the call carried a real credential, and whether the model ever held the name, card and token. They also differ on who turns a token back into a real value: a time bound on Infisical's pages, a named person approving the action in RedactSure's design (What Is Supervised Delegation?).
What does Infisical protect, and where does it act?
Infisical Agent Vault is an open-source credential proxy and vault for agents, built for an agent that has to reach a service without carrying the value that opens it. The overview states the design plainly: "Forward proxies that intercept an AI agent's requests and attach real credentials on the way out," and adds "Time-bound grants that let AI agents access services without holding real credentials" (Infisical, Documentation, 2026).
"In a traditional proxy, that tunnel remains opaque, simply forwarding encrypted traffic," which is why "Agent Vault terminates TLS" and the proxy places the real credential in the request (Infisical, Proxy, 2026). The pressure is measurable: Help Net Security, reporting GitGuardian's data, records "28,649,024 new secrets exposed in public GitHub commits across 2025" (Help Net Security, 2026).
Each benefit depends on one condition: the request goes through the proxy, and the grant covers the service it reaches. The boundary is the screen. A proxy that terminates TLS sees a request and rewrites it, and it generates nothing for a page the model reads first. An application that renders a customer record does so outside that path, so the record arrives in the model's context intact. That is a limit of the design, and it is where an agent that reads before it acts begins.
What does an agent read when it opens a customer account in a support console?
The record is a customer account in a support console the organization bought, and the same run opens the settings page beside it for an API token. The account page shows a name, an email address, the card number on file and a call note; the settings page shows the token.
Infisical's control reaches the request the agent makes with that token, not the page. A forward proxy attaches a real credential to an outbound call, and no grant changes what the application draws before the call exists. The model receives the record as the console renders it.
Data minimisation points the other way: personal data must be "adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed" (Regulation 2016/679, 2016). A name, an email and a card number are more than a delivery question needs.
The consequence outlasts the run, since the SEC's 2024 amendments require an incident response program for unauthorized access to customer information and generally "notify affected individuals within 30 days" (SEC, 2024).
Two records disagree. The console logs the support lead whose session the agent used, the identity gap What Is a Tethered Agent? describes: no account for the agent. Can a Credential Vault Protect What an AI Agent Reads? puts the point plainly: enterprise records are encountered rather than deposited.
The agents' own documentation draws the line at the credential: 9 of the 15 reviewed keep passwords or credentials away from the model, against 0 that do the same for the customer data the screen shows, from vendor documentation read October 22 to 27, 2026 rather than a test (Do AI Agents Ask Before Making a Payment?).
Which control fits which work?
Each product is the better fit for a different job, and both jobs exist in the same organization.
Keep Infisical for
- An agent that reaches a service without holding the value that opens it, where "Time-bound grants" set the reach (Infisical, Documentation, 2026).
- A workflow whose main risk is a credential in the agent's process, since the proxy inserts the real value into the request (Infisical, Proxy, 2026).
- A team that wants an open-source proxy it runs itself, as "The Open Source Credential Proxy and Vault for Agents" describes (Infisical, Proxy, 2026).
Add RedactSure for
- Agents reading screens in applications the organization bought, where the model receives CUST_001 and nothing is installed inside the application (What Is Render-Layer Tokenization?).
- A named person on the record for every payment, submission or change the agent proposes (What Is Supervised Delegation?).
- The record of what the model received on each screen, exported to the customer's SIEM (What Is an AI Control Record?).
Most teams running agents end up with both, and this block names the one that covers the screen.
How do you test it on one workflow?
Book one afternoon, put both vendors in front of the same workflow, and write each answer down before the next question.
Step 1. Choose one screen the agent will actually open, such as the customer account page, not a diagram of the data flow.
Step 2. Ask each vendor to replay the model's input for that screen, field by field, and save it. It shows whether the model saw real values or stand-ins, and where a stand-in was resolved.
Step 3. List every application the workflow touches and mark each as reached through the proxy, rendered inside the governed environment, or neither. The last group is the exposure on day one, and that count belongs in the plan.
Step 4. Trace the token back to what released the real value, for which destination, and whose name sits in the record. A short-lived credential answers when a value expires, not who approved the action: HashiCorp's tutorial states that "Token lifetime is reduced from days or weeks to minutes" and that a wrapper script "exports it as VAULT_TOKEN, and launches the agent" (HashiCorp, 2026).
Step 5. Calculate first-day coverage. If the workflow touches six applications and the proxy covers two, coverage is two of six. Compare the costs that differ: routing work, and the agent work held up until it is finished.
What does a governed environment change?
A governed environment is a category of control rather than a product feature. The agent works under its own session and identity, and it sees a different screen because values are replaced with consistent tokens before the model reads anything. The customer appears as CUST_001, with CARD_001 and TOKEN_001, on every page of the run. Real values resolve only at approved destinations at the moment of an approved action, a named person approves every payment, submission and record change, and each screen, action and approval goes to a record exported to the organization's SIEM.
The design answers a question the authorization layer asks later. Arcade states it for one action: "Can this agent, acting for this user, perform this action on this resource?" (Arcade, 2025). By the time it is asked, the agent has read the page and the record sits in its context, so a substitution made before the reading changes what the question is about.
A time limit answers a different part of it. Bounding how long a credential works says nothing about who approved the action, so the substitution and the record carry weight a duration cannot.
What the record shows
The record on the support console carries a customer's name, email address, card number and call note, and the settings page beside it carries an API token in full. A render-layer control rewrites those fields into CUST_001, CARD_001 and TOKEN_001 before the model reads the screen, and RedactSure, as the Infisical alternative for agent work, performs the substitution, with real values resolving only at the destination a named person approved. Infisical's coverage is the outbound call its proxy attaches a credential to, which answers for a request and leaves the page to whatever renders it. One screen is the whole test: open it with both products installed, then follow the token back to the approval that released it.
Methodology and limitations
This page rests on two Infisical pages, HashiCorp's Vault tutorial, Arcade's post on agent authorization, Help Net Security's report on GitGuardian's data, the SEC's press release and GDPR Article 5(1)(c), with existing RedactSure research pages. Vendor pages were read between October 20, 2026 and October 21, 2026, and each Sources line carries the date for its page. Quoted statements appear in the vendor's own wording, and public documentation read in full gives a sound view of where each product applies its control; a statement that a source does not describe something refers to the pages reviewed.
The products here are described from documentation; none was tested for this page, and no customer of either is described. Documentation describes intended design, both products change, and the page carries its date. RedactSure is deploying now with enterprise and government customers. The customer account and the token are an illustrative record type, not an organization. Compliance determinations belong to the organization's counsel, assessors and security team, and nothing here replaces a pilot of one workflow on its own screens.
Frequently asked questions
Does Infisical protect the customer data an agent reads on a screen?
No. Infisical's pages describe a proxy that attaches a credential to a request and a time-bound grant, and neither sits between the console and the model. The customer record renders in the application, and the model reads what the application draws. A control at the network edge reaches the call that follows, so the record is already in context.
What does Infisical Agent Vault cover when an agent calls an API?
The outbound call. A forward proxy attaches the credential to the request the agent makes, and a time-bound grant sets how long that reach lasts. That covers the stolen-credential case, because the agent process never holds the stored value. It says nothing about a value the application renders, such as a token on a settings page.
Who approves the agent's action, a grant or a person?
A grant, on Infisical's pages. The overview issues a time-bound grant that lets an agent reach a service, and the duration is the limit it documents. It is set in advance and covers whatever the agent does inside it. A named person approving each payment, submission or record change is a different control, and a buyer should know which one the workflow needs.
What record shows what the model read on that screen?
Not from the pages reviewed. The overview and the post describe a proxy, a grant and TLS termination at the proxy; neither describes a record of the screen the model received (Infisical, Documentation, 2026). The application's log records the employee whose session the agent used, which is the identity gap. A record that answers the question has to be written where the page is drawn.
Is a credential proxy the same as a control on the page?
No. A proxy terminates TLS and inserts a value into a request, which "removes the secret from the agent and puts the plaintext in the proxy," as one RedactSure page puts it (Can a Vendor Read Credentials Encrypted to My Own Key?). That protects a call and a deposited value. A rendered page is not a deposit: the application draws it on every run, and no vault has an entry for that customer.
Can a team keep Infisical and still close the screen gap?
Yes. Most teams keep it for the calls an agent makes with a credential, because a proxy that never lets the agent hold the stored value is a good control for that exposure. The screen is the part its pages do not cover, and RedactSure covers it by replacing values before the model reads them. A team can run both.
How RedactSure closes the screen gap a credential proxy leaves
An agent reads the customer account before it sends anything, and a proxy attaches credentials to the request after that reading. Infisical's post is explicit that "the agent should not be trusted with direct access to any secrets," which is why it terminates TLS and keeps the value there (Infisical, Proxy, 2026).
The environment that enforces this is built by RedactSure, an AI agent controls, governance and data protection company.
Before: the agent opens the support console under the team lead's session, the account page shows the name, email, card number and call note and the settings page the API token. Inside: the pages show CUST_001, CARD_001 and TOKEN_001, real values reach only the approved destination, and the lead's approval of the refund is recorded.
RedactSure is deploying now with enterprise and government customers.
Everyone else controls where data can go. RedactSure controls what the AI can see.
See it on your own workflow
Protecting the sensitive data an agent could read on a screen is a needed part of any solution that includes Infisical. Bring one customer account and see, with test values, what the model reads and who approves the refund. Book a demo